Principal Investigator: Dr Michael Inouye
Department: Baker Heart and Diabetes InstituteTags: 55469, cardiovascular, causal inference, genetics/genotyping, metabolic, prediction
Cardiometabolic diseases are the leading cause of death and morbidity worldwide. In number of deaths, they are followed by their complications, such as kidney disease, heart attack and stroke as well as neurological conditions, such as Alzheimer’s disease. Together, they are responsible for the most deaths and the highest costs in the world in terms of treatments and hospitalisation. These conditions are caused by both genetics (inherited DNA) and environment (diet, activity, sleep).
In our research we aim to investigate (i) critical genes, regulatory regions and their interactions that influence risk of the disease; (ii) the complex interplay, between the genes and environment, that underpins both health, and risk of developing diseases; (iii) understand the causal mechanisms, biomarkers and progression of disease in order to develop new and improved treatments; and (iv) determine genetic risk of metabolic diseases.
We will use the genetic information and wide variety of disease and other phenotypes available in UK Biobank, such as biomarkers and imaging data.
Despite advances in prediction as well as changes in lifestyle and medication these diseases are still on the rise globally. Key challenges in the prevention and management are to: (i) understand better the complex molecular pathways and mechanisms leading to their development, progression, and complications; (ii) determine the causal relation of biomarkers and other putative risk factors, and (ii) find new therapeutic approaches to reduce deaths due to those disorders.
Our proposal will (i) improve understanding of the genetic mechanisms of cardiometabolic and neurological diseases and their comorbidities; (ii) provide a better understanding of how genetics interact with environmental factors in development and progression of these conditions; (iii) and potentially lead to improving their prediction, prevention and treatment.